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Beautiful ridgeline plots in Python
visualization python data-science plotly plot data-visualization graphing data-analysis plotting joyplot ggridges ridgeline distplot
Seaborn is one of the go-to tools for statistical data visualization in python. It has been actively developed since 2012 and in July 2018, the author released version 0.9. This version of Seaborn has several new plotting features, API changes and documentation updates which combine to enhance an already great library. This article will walk thr…
heatmap data-visualization seaborn boxplot violinplot ipython-notebooks facetgrid python-visualization scatterplot-visualization barplots seaborn-plots lmplot seaborn-tutorial distplot stripplots python-seaborn seaborn-image python4everybody python4datascience tutor-milaan9
Assignment-04-Simple-Linear-Regression-2. Q2) Salary_hike -> Build a prediction model for Salary_hike Build a simple linear regression model by performing EDA and do necessary transformations and select the best model using R or Python. EDA and Data Visualization. Correlation Analysis. Model Building. Model Testing. Model Predictions.
python numpy smf eda pandas data-visualization seaborn p-value model-predictions feature-engineering ols-regression statsmodels model-building simple-linear-regression correlation-analysis t-score model-testing distplot regression-plot r-square-values
Assignment-04-Simple-Linear-Regression-1. Q1) Delivery_time -> Predict delivery time using sorting time. Build a simple linear regression model by performing EDA and do necessary transformations and select the best model using R or Python. EDA and Data Visualization, Feature Engineering, Correlation Analysis, Model Building, Model Testing and Mo…
python numpy smf eda pandas data-visualization seaborn p-value model-predictions feature-engineering ols-regression statsmodels model-building simple-linear-regression correlation-analysis rsquare-values t-score model-testing distplot regression-plot
Q 21) Check whether the data follows normal distribution a) Check whether the MPG of Cars follows Normal Distribution
Supervised-ML---Simple-Linear-Regression---Newspaper-data. EDA and Visualization, Correlation Analysis, Model Building, Model Testing, Model predictions.
visualization python api smf eda pandas seaborn goodness-of-fit hypothesis-testing ols-regression statsmodels simple-linear-regression correlation-analysis significance-testing rsquare-values distplot regplot
Supervised-ML---Simple-Linear-Regression---Waist-Circumference-Adipose-Tissue-Data. EDA and data visualization, Correlation Analysis, Model Building, Model Testing, Model Prediction.
visualization python smf eda pandas seaborn p-value model-predictions goodness-of-fit ols-regression statsmodels simple-linear-regression correlation-analysis t-score distplot determination-coefficient r-square-values regplot
Visualization using Matplotlib and Seaborn
histogram python3 seaborn matplotlib boxplot swarmplot densityplot matplotlib-tutorial barplot violinplot jointplot pairplot matplotlib-pyplot seaborn-plots seaborn-tutorial distplot stripplots pieplot seaborn-image combined-plots
Higher Diploma in Science in Computing (Data Analytics) - Programme Module: Fundamentals of Data Analysis (COMP08050)
simulation numpy pandas-dataframe jupyter-notebook scipy scatter-plot distributions synthetic-data airlines gumbel barplots distplot stripplots
Python matplotlib, seaborn and plotly plots cheat sheet
python pie-chart plotly histogram seaborn scatter-plot matplotlib boxplot iris-dataset barplot 3d-scatter-plot pairplot googlecolab distplot clustermap
Suppose GMAT scores can be reasonably modeled using a normal distribution with mean=711 and SD = 29. What is P(X<=680) What is P(697<=X<=740)
Comparison between Marvel and DC in terms of their Characters Popularity, their Gender, Hair Color, Eye Color, Character Alignment, Appearances, Launch day, names, etc. I have used Seaborn, matplotlib, networkx, and plotly to visualize Interactive plots
plotly data-visualization comics seaborn networkx data-analysis marvel network-visualization dc boxplot barplot 3dplot distplot
Normal-Distribution
numpy mean pandas python3 seaborn matplotlib dataframes standard-deviation matplotlib-pyplot matplotlib-python seaborn-plots distplot
Seaborn Visualization on Titanic Dataset Visual exploration of different features on No. of people survived or otherwise Visualization using FacetGrid function, Lambda function and criterion function Visualization of subplots
python numpy lambda-functions pandas seaborn criteria boxplot groupby barplot facetgrid pairplot subplots distplot
Q1) Delivery_time -> Predict delivery time using sorting time. Build a simple linear regression model by performing EDA and do necessary transformations and select the best model using R or Python. EDA and Data Visualization, Feature Engineering, Correlation Analysis, Model Building, Model Testing and Model Predictions using simple linear regressi
python numpy smf eda pandas data-visualization seaborn p-value feature-engineering ols-regression model-building simple-linear-regression correlation-analysis rsquare-values t-score statsmodel model-testing distplot model-prediction regression-plot
👩🏻🍳🍽️Restaurant Success Prediction using ML
machine-learning data-visualization sqlite3 outlier-detection restaurant feature-engineering feature-importance random-forest-classifier feature-encoding distplot hypertuning one-hot-encoding wordcloud-visualization grid-search-cross-validation success-prediction handling-outlier histplot data-cleaning-and-preprocessing model-building-and-evaluation randomised-search-cross-validation
Q 21) Check whether the data follows normal distribution a) Check whether the MPG of Cars follows Normal Distribution Dataset: Cars.csv
Used libraries and functions as follows:
python numpy smf eda pandas data-visualization seaborn p-value model-predictions feature-engineering ols-regression model-building simple-linear-regression correlation-analysis t-score model-testing distplot statmodels regression-plot r-square-values
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